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Displaying posts with tag: scaling (reset)

MySQL 5.4 Scaling on Nehalem with Sysbench
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As a final followup to my MySQL 5.4 Scalability on 64-way CMT Servers blog, I'm posting MySQL 5.4 Sysbench results on a Sun Fire X4270 platform using the Intel x86 Nehalem chip (2 sockets/8 cores/16 threads). All CPUs were turned on during the runs. The my.cnf was the same as described in the previous blog.

The Sysbench version used was 0.4.12, and the read-only runs were invoked with the following command:

sysbench --max-time=300 --max-requests=0 --test=oltp --oltp-dist-type=special --oltp-table-size=10000000 \\
   --oltp-read-only=on --num-threads=[NO_THREADS] run

The "oltp-read-only=on" parameter was omitted for the read-write tests. The my.cnf file listed in my previous blog was also used unchanged for these tests.

Here are the results graphically running on Linux.

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MySQL 5.4 Sysbench Scalability on 64-way CMT Servers
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As a followup to my MySQL 5.4 Scalability on 64-way CMT Servers blog, I'm posting MySQL 5.4 Sysbench results on the same platform. The tests were carried out using the same basic approach (i.e. turning off entire cores at a time) - see my previous blog for more details.

The Sysbench version used was 0.4.8, and the read-only runs were invoked with the following command:

sysbench --max-time=300 --max-requests=0 --test=oltp --oltp-dist-type=special --oltp-table-size=10000000 \\
   --oltp-read-only=on --num-threads=[NO_THREADS] run
The "oltp-read-only=on" parameter was omitted for the read-write tests. The my.cnf file listed in my previous blog was also used unchanged for these tests.

Here is the data presented graphically. Note that the number of vCPUs is the same as the number of

  [Read more...]
MySQL 5.4 Sysbench Scalability on 64-way CMT Servers
Employee +0 Vote Up -0Vote Down
As a followup to my MySQL 5.4 Scalability on 64-way CMT Servers blog, I'm posting MySQL 5.4 Sysbench results on the same platform. The tests were carried out using the same basic approach (i.e. turning off entire cores at a time) - see my previous blog for more details.

The Sysbench version used was 0.4.8, and the read-only runs were invoked with the following command:

sysbench --max-time=300 --max-requests=0 --test=oltp --oltp-dist-type=special --oltp-table-size=10000000 \\
   --oltp-read-only=on --num-threads=[NO_THREADS] run
The "oltp-read-only=on" parameter was omitted for the read-write tests. The my.cnf file listed in my previous blog was also used unchanged for these tests.

Here is the data presented graphically. Note that the number of vCPUs is the same as the number of

  [Read more...]
MySQL 5.4 Scalability on 64-way CMT Servers
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Today Sun Microsystems announced MySQL 5.4, a release that focuses on performance and scalability. For a long time it's been possible to escape the confines of a single system with MySQL, thanks to scale-out technologies like replication and sharding. But it ought to be possible to scale-up efficiently as well - to fully utilize the CPU resource on a server with a single instance.

MySQL 5.4 takes a stride in that direction. It features a number of performance and scalability fixes, including the justifiably-famous Google SMP patch along with a range of other fixes. And there's plenty more to come in future releases. For specifics about the MySQL 5.4 fixes, check out Mikael Ronstrom's blog.

So how well does MySQL 5.4 scale? To help answer the question I'm going to take a look at some performance data from one of Sun's CMT

  [Read more...]
MySQL 5.4 Scalability on 64-way CMT Servers
Employee +0 Vote Up -0Vote Down
Today Sun Microsystems announced MySQL 5.4, a release that focuses on performance and scalability. For a long time it's been possible to escape the confines of a single system with MySQL, thanks to scale-out technologies like replication and sharding. But it ought to be possible to scale-up efficiently as well - to fully utilize the CPU resource on a server with a single instance.

MySQL 5.4 takes a stride in that direction. It features a number of performance and scalability fixes, including the justifiably-famous Google SMP patch along with a range of other fixes. And there's plenty more to come in future releases. For specifics about the MySQL 5.4 fixes, check out Mikael Ronstrom's blog.

So how well does MySQL 5.4 scale? To help answer the question I'm going to take a look at some performance data from one of Sun's CMT

  [Read more...]
Predictive caching in a MySQL-backed infrastructure
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Sounds a bit far fetched (pun intended ;-), but we're doing it. This is not inside of the MySQL server, but rather the overall application design. Let me run you through the logic...

Some key aspects to scaling are: not doing unnecessary queries, and caching what you can. Just a quick baseline. The fastest query is the one you don't do, or the one you've already done before - the latter being caching.

A simple yet brilliant example of this is the Youtube trick where a script reads the relay log, converting updates into appropriate selects and running them so that the InnoDB cache will have the blocks in memory when the slave SQL thread executes the actual update. Maatkit now has a tool for this, so it's publically available. It's not quite predictive, but it's a neat trick anyway that sometimes comes in handy. Search engines use similar tricks.

Extending on this, with





  [Read more...]
Predictive caching in a MySQL-backed infrastructure
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Sounds a bit far fetched (pun intended ;-), but we’re doing it. This is not inside of the MySQL server, but rather the overall application design. Let me run you through the logic…

Some key aspects to scaling are: not doing unnecessary queries, and caching what you can. Just a quick baseline. The fastest query is the one you don’t do, or the one you’ve already done before - the latter being caching.

A simple yet brilliant example of this is the Youtube trick where a script reads the relay log, converting updates into appropriate selects and running them so that the InnoDB cache will have the blocks in memory when the slave SQL thread executes the actual update. Maatkit now has a tool for this, so it’s publically available. It’s not quite predictive, but it’s a neat trick anyway that sometimes comes in handy. Search engines

  [Read more...]
Solving the PBXT DBT2 Scaling Problem
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One little bit of wisdom I would like to pass on:

If a program runs fast with 20 threads, that does not mean it will run fast with 50. And if it runs fast with 50, it does not mean that it will run fast with 100, and if it runs fast with 100 ... don't bet on it running fast with 200 :)

In my last blog I discussed some improvement to the performance of PBXT running the DBT2 benchmark. Despite the overall significant increase in performance I noted a drop off at 32 threads that indicated a scaling problem. For the last couple of weeks I have been working on this problem and I have managed to fix it:

As before, this test was done





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BFT: Our case for 100% de-normalization.
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As a long time DBA and Database Architect this idea is repugnant – make a database 100% de-normalized; one table and except for the one query, retrieval by primary key, nothing else works.  And yet we have had great success using this kind of database.

This does not replace the original normalized database, rather it is more like a permeant cache fed from the main database.  It is a MySQL (http://mysql.com/) database which has certain advantages over Memcached or other true caches such as it is permanent until our processes replace it.

Consider what it might take to build a simple web page: get a request, process it which might take many queries and some significant processing then send back your html.

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Don’t fix, work around – MySQL
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Sun decided to not go down the route of reviewing and accepting the patches, but are now suggesting - are you sitting down? - running multiple instances on the same hardware.
10 Newer Entries Showing entries 31 to 40 of 66 10 Older Entries

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